CN111242773A

CN111242773A - Virtual resource application docking method and device, computer equipment and storage medium

Info

Publication number: CN111242773A
Application number: CN202010045522.9A
Authority: CN
Inventors: 赵成龙
Original assignee: OneConnect Financial Technology Co Ltd Shanghai
Current assignee: OneConnect Smart Technology Co Ltd; OneConnect Financial Technology Co Ltd Shanghai
Priority date: 2020-01-16
Filing date: 2020-01-16
Publication date: 2020-06-05

Abstract

The invention discloses a docking method, a docking device, computer equipment and a storage medium for virtual resource application, wherein the docking method comprises the following steps: receiving a virtual resource application user's incoming application, carrying out information verification and wind control preliminary review on the virtual resource application user, and sending the incoming application to the adapted virtual resource main body for credit application through an intelligent recommendation system when the virtual resource application user passes the information verification and wind control preliminary review. The docking method, the docking device, the computer equipment and the storage medium for the virtual resource application can realize intelligent information verification and wind control initial review on the incoming application and send the incoming application to a proper virtual resource main body for credit application, can greatly improve the service capability and the service efficiency of the virtual resource main body, and are beneficial to reducing the cost of acquiring resources by the virtual resource main bodies such as small and medium-sized micro enterprises.

Description

Virtual resource application docking method and device, computer equipment and storage medium

Technical Field

The invention relates to a method and a device for docking a virtual resource application, computer equipment and a storage medium.

Background

As an important component of the economy of China, the final product and service value created by small and medium-sized micro-enterprises account for 60% of the total production value in China, and the method also has outstanding contribution in the aspect of promoting employment, but the small and medium-sized micro-enterprises have obvious disadvantages in the aspect of resource acquisition capacity, and particularly, for the important resource of capital, a series of problems of 'difficulty in financing, high financing cost, disorder in financing, financing risk' and the like squeeze the living space of the small and medium-sized micro-enterprises, and the small and medium-sized micro-enterprises want to continue to expand the reproduction, rely on slow endogenous accumulation, or are forced to carry out folk loan. Taking loan as an example, currently, small and medium-sized enterprises need to submit incoming applications to banks sequentially through online platforms of the banks at user terminals, and staff at the bank terminals need to check and examine the incoming applications received through the internet in sequence.

Disclosure of Invention

In view of this, the present invention provides a virtual resource application docking method, an apparatus, a computer device, and a storage medium, which can effectively improve efficiency and a wind control level of virtual resource application docking between a virtual resource application user and a virtual resource subject, such as a small and medium-sized micro enterprise.

Firstly, in order to achieve the above object, the present invention provides a docking method for virtual resource application, which is applied to a docking device for virtual resource application, and the method includes

Receiving a file-in application of a virtual resource application user;

carrying out information verification and wind control preliminary examination on the virtual resource application user;

and when the virtual resource application user passes the information verification and wind control initial review, sending the incoming application to the adaptive virtual resource main body for credit application through an intelligent recommendation system.

Further, the sending the incoming application to the adapted virtual resource main body through the intelligent recommendation system for credit application includes

Comparing the data of each condition of the virtual resource application user with the conditions of each virtual resource product of each virtual resource main body or the historical record data of each virtual resource main body to obtain the matching degree of each virtual resource main body;

and sending the incoming application to the virtual resource main body with the highest matching degree to serve as a credit application.

Further, the step of obtaining the matching degree of each virtual resource product further comprises

Screening out a virtual resource main body with the matching degree higher than a set threshold value;

sorting the virtual resource bodies meeting the conditions from high to low according to the matching degree;

after sending the incoming application to the virtual resource main body with the highest matching degree to make a credit application, the method also comprises the step of

Receiving feedback information of the virtual resource main body and judging whether the credit application passes the approval or not;

and when the approval of the approval application is not passed, sending the incoming application to a virtual resource main body with a lower matching degree by one level to make the approval application until the approval of the virtual resource main body is passed or all the virtual resource main bodies with the matching degrees higher than a set threshold value are not approved and passed.

Further, the information verification of the virtual resource application user comprises

Checking whether the user information contained in the incoming application is correct or not;

when the user information contained in the incoming application is verified correctly, transmitting verification information to the virtual resource application user through a verified reliable path for secondary verification;

receiving secondary verification information fed back by a virtual resource application user and judging whether the secondary verification information meets the conditions or not;

and when the secondary verification information fed back by the virtual resource application user meets the condition, passing the information verification.

Further, the wind control preliminary examination comprises

And auditing each operation data contained in the user information contained in the incoming application, and judging whether abnormal data exist in the operation data.

Further, the auditing the operation data contained in the user information contained in the article-feeding application and the judging whether the abnormal data exists in the operation data comprise

Extracting industry information and main operation product information in the user information;

capturing a reference range of each operation data of the corresponding industry and the main operation products from the public database;

and sequentially judging whether each operation data falls in the reference range, if so, judging the operation data to be normal data, and otherwise, judging the operation data to be abnormal data.

Further, the auditing each operation data contained in the user information contained in the article-feeding application and the judging whether the operation data has abnormal data also comprise

When abnormal data exists, generating a supplementary certificate file list according to the abnormal data;

sending the supplementary certificate list to a virtual resource application user;

receiving a supplementary certificate of a virtual resource application user;

verifying the credibility and the validity of the supplementary certificate file through the operation instruction of the user;

and when the credibility and the validity of the supplementary certification file both meet the conditions, judging that the virtual resource application user passes the wind control initial review.

In order to achieve the above object, the present invention further provides a docking device for virtual resource application, which comprises

The receiving module is suitable for receiving the incoming application of the virtual resource application user;

the initial review module is suitable for carrying out information verification and wind control initial review on the virtual resource application user;

and the intelligent routing module is suitable for sending the incoming application to the adaptive virtual resource main body for credit application through an intelligent recommendation system when the virtual resource application user passes the information verification and wind control initial review.

In order to achieve the above object, the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the docking method of the virtual resource application when executing the computer program.

To achieve the above object, the present invention also provides a computer-readable storage medium having a computer program stored thereon, characterized in that: the computer program, when executed by a processor, implements the method of interfacing virtual resource applications described above.

Compared with the prior art, the virtual resource application docking method, the virtual resource application docking device, the computer equipment and the storage medium can realize intelligent information verification and wind control initial review on the incoming application and send the incoming application to a proper virtual resource main body for credit application, can greatly improve the service capacity and service efficiency of the virtual resource main body, and is beneficial to reducing the cost of acquiring resources by the virtual resource main bodies of small and medium-sized micro enterprises and the like.

Drawings

FIG. 1 is a diagram of an alternative application environment for a docking device for an enterprise loan application, in accordance with various embodiments of the invention;

FIG. 2 is a flowchart illustrating a method for docking an enterprise loan application according to a first embodiment of the invention;

FIG. 3 is a schematic flow chart illustrating a process of sending the incoming application to an adapted bank for a credit application through an intelligent recommendation system according to an embodiment of the present invention;

FIG. 4 is a schematic flow chart illustrating the information verification performed by the loan application enterprise according to the embodiment of the invention;

FIG. 5 is a schematic flow chart of a wind-controlled preliminary examination according to an embodiment of the present invention;

FIG. 6 is a schematic diagram illustrating a process of auditing each business data included in enterprise information according to an embodiment of the present invention;

FIG. 7 is a schematic flow chart of a wind-controlled preliminary examination according to an embodiment of the present invention;

FIG. 8 is a block diagram of a process of a docking device for an enterprise loan application in accordance with a second embodiment of the invention;

fig. 9 is a schematic hardware configuration diagram of a computer device according to a third embodiment of the present invention.

Reference numerals

Applied for loan in an enterpriseDocking device	100、904
		Receiving module	101
Preliminary examination module	102
		Intelligent routing module	103
Computer equipment	900
		Memory device	901
Processor with a memory having a plurality of memory cells	902
		Network interface	903

The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that the description relating to "first", "second", etc. in the present invention is for descriptive purposes only and is not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.

In addition, it should be noted that, because the variety of virtual resources is various, for convenience of understanding and description, the following embodiments are developed by taking a case where a small and medium-sized micro enterprise loans into a bank as an example, so in the following embodiments, a virtual resource application user corresponds to the small and medium-sized micro enterprise, a virtual resource subject corresponds to the bank, a virtual resource product corresponds to a financial product, a virtual resource application corresponds to an enterprise loan application, and a docking device of the virtual resource application corresponds to a docking device of the enterprise loan application.

Fig. 1 is a schematic diagram illustrating an alternative application environment of a docking device 100 (hereinafter, referred to as "docking device 100") for an enterprise loan application according to various embodiments of the present invention.

In this embodiment, the docking device 100 may connect the enterprise terminal 200 at the upstream and the bank terminal 300 at the downstream in a wired or wireless manner, the docking device 100 may communicate with each enterprise terminal 200 and each bank terminal 300, the user at the upstream may send a feeding application to the docking device 100 through the enterprise terminal 200, the docking device 100 processes the received feeding application and sends a feeding application meeting the setting requirement to the bank terminal 300 at the downstream, the docking device 100 plays a role of connecting a bridge between the enterprise terminal 200 and the bank terminal 300, and is intended to pre-screen and pre-determine a large number of feeding applications, so that the feeding application meeting the condition is sent to the bank terminal 300 at the downstream, thereby improving the efficiency of docking between the enterprise and the bank.

The forms of the enterprise terminal 200 and the bank terminal 300 include, but are not limited to, common office facilities such as a PC computer, a notebook computer, a mobile phone, a tablet computer, and the like, and may also be communication terminals specially customized and produced according to requirements.

The hardware structure and functions of the apparatus according to the present invention have been described so far. Various embodiments of the present invention will be presented based on the above description.

First, the present invention provides a method for docking an enterprise loan application according to a first embodiment.

Example one

The method for docking the enterprise loan application is implemented by the docking device 100, and comprises the following steps S401 to S403:

step S401, receiving a request for sending a loan application enterprise;

in this step, the incoming application includes information that can reflect the basic situation of the loan application enterprise, such as the basic information of the loan application enterprise, the affiliated industry, the main product, and the operating situation, and also includes the specific loan detail information such as the required loan amount and the loan purpose of the loan application enterprise, and the loan application enterprise personnel generally submits the incoming application in a form of filling in relevant information and uploading corresponding vouchers on line at the enterprise terminal 200, or submits the incoming application in a form of mail or the like.

Step S402, carrying out information verification and wind control preliminary examination on the loan application enterprises, and jumping to step S403 when the loan application enterprises pass the information verification and wind control preliminary examination;

in the step, the information verification process is used for verifying whether basic information of the loan application enterprise is correct, the legality of a login path of an enterprise user and the like, the wind control initial review process is used for preliminarily evaluating the risk degree of the loan application enterprise according to information of the enterprise, such as the industry, main operation products, operation conditions and the like and other available public information, and part of loan application enterprises with high obvious risk can be screened out through the wind control initial review process, so that the subsequent processing flow is saved, and the application of computing resources and subsequent bank audit resources to future piece-feeding applications without prospects is avoided.

And S403, sending the incoming application to an adaptive bank for credit application through an intelligent recommendation system.

In this step, the intelligent recommendation system is an intelligent recommendation system for a bank that is suitable for intelligent recommendation according to the self condition of the loan application enterprise, and sends the incoming application of the enterprise to the bank terminal 300 of the corresponding bank, and the bank terminal 300 staff further checks the received credit granting application.

Here, the intelligent recommendation system is a recommendation algorithm. Because of different types of customers, the bank does not have specific standards for selecting enterprises capable of making loans, the bank puts out a series of financial products for the enterprises to select adaptive applications, and various financial products can meet the loan requirements of various enterprises such as large, medium and small enterprises, so that the matching degree between the conditions of the enterprises and the financial products of the bank needs to be firstly seen to recommend the incoming applications of the enterprises to the adaptive bank. Based on this, the main work of the intelligent recommendation system includes: firstly, calculating the matching degree between the enterprises and the financial products by contrasting the conditions of the financial products of each bank, wherein the matching degree can be calculated by using a fuzzy matching algorithm, and the matching degree calculated by using the fuzzy matching algorithm has better tolerance, so that the incoming application of the enterprises can be adapted to more financial products, and the financial products with not very large condition difference are prevented from being missed; then, according to the calculated matching degree, financial products are screened, and financial products with higher matching degree are screened out; and finally, looking at which bank the financial product with higher matching degree is released, namely, which bank the incoming application of the enterprise is sent to. By the mode, the financial products are used as the standard, the matching degree is used as the adaptation condition, the enterprises can be recommended to the adapted bank accurately, and the successful probability of loan is improved. Referring to fig. 2, the process of step S403 may specifically refer to steps S501 to S502 as follows:

step S501, comparing the data of each condition of the loan application enterprise with the conditions of each financial product of each bank or the historical loan record data of each bank to obtain the matching degree of each bank;

in this step, the intelligent recommendation system collects financial products released by each bank for small and medium-sized micro-enterprises, and compares and matches the financial products according to the information contained in the incoming application and the conditions of the financial products, and in one embodiment, the intelligent recommendation system calculates the matching degree of the incoming application and each financial product as follows, steps a1-a 5:

step A1, obtaining financial products meeting the conditions according to the data of the required loan amount in the incoming application and the preset pre-screening rules;

the pre-screening rule can be that whether the required loan amount of the enterprise falls in the loan amount interval which can be provided by the financial product is judged, if so, the corresponding financial product is brought into the financial product sequence to be selected, otherwise, the financial product is skipped to judge the next financial product; the pre-screening rules are simple and may result in the loss of a suitable financial product, so in a preferred embodiment, the following pre-screening rules may be used: firstly, the intelligent recommendation system multiplies the required loan limit by a preset interval to obtain a required limit interval, then the intelligent recommendation system judges whether the required limit interval and the loan limit interval of the financial product have an overlapping part, if so, the corresponding financial product is brought into a financial product sequence to be selected, and if not, the financial product is skipped to judge the next financial product. Examples are as follows: if the condition of the loan amount which can be provided by the financial product A is not more than 1000 ten thousand, namely the loan amount interval is (0, 1000 ten thousand), the required loan amount of an enterprise is 1200 ten thousand, when in pre-screening, if the preset interval is [0.8,1.2], the required amount interval obtained by multiplying the required loan amount by the preset interval is [960 ten thousand, 1440 ten thousand ], then the overlapping part of the loan amount interval and the required amount interval can be found by comparing the loan amount interval and the required amount interval, the financial product A can be brought into a financial product sequence to be selected, thus more financial products meeting the requirement can be matched, and for each financial product in the financial product sequence to be selected, the following matching steps A2-A5 are executed:

step A2, acquiring condition information of financial products, and extracting data items contained in the condition information and numerical conditions corresponding to the data items;

for example, if the conditions of financial product B are as follows: (1) the registered fund of the enterprise is not less than 1000 ten thousand; (2) the establishment period of the enterprise is not less than 3 years; (2) the annual sales volume of the enterprise is not less than 800 ten thousand; the obtained data items and numerical conditions are as shown in the following table:

data item	Numerical conditions
		Registering funds	Not less than 2000 ten thousand
Year of establishment	More than or equal to 3 years
		Sales volume in last year	Not less than 1500 ten thousand

Step A3, extracting corresponding data items and corresponding numerical values from the incoming application;

for example, the registered fund of a certain enterprise is 1800 thousands, the established year is 4 years, and the annual sales volume in the last year is 1200 thousands; the corresponding data items and the corresponding values extracted in the incoming application are shown in the following table:

data item	Numerical value
		Registering funds	1800 million
Year of establishment	4 years old
		Sales volume in last year	1200 ten thousand

Step A4, calculating a first quantifiable interval according to the critical value of the numerical condition of the data items, and calculating the matching degree of each data item according to a first quantification function;

taking the data item of the registered fund as an example, the algorithm of the first quantifiable interval is to multiply the critical value of the numerical condition by the first expansion factor interval, if the first expansion factor interval is preset to be (0.6,1), the first quantifiable interval is (1200 ten thousand, 2000 ten thousand), the meaning of the first quantifiable interval is that when the registered fund of the loan application enterprise is less than 1200 ten thousand, the matching degree is 0, when the registered fund of the loan application enterprise is greater than or equal to 2000 ten thousand, the matching degree is 1, when the registered fund of the loan application enterprise is in the first quantifiable interval, the matching degree is calculated according to the first quantifiable function, if the preset first quantifiable function makes the matching degree (0,1) uniformly distributed in the interval (1200 ten thousand, 2000 ten thousand), the matching degree corresponding to the 1800 registered fund of the loan application enterprise can be calculated to be 0.75.

By the same method, if the first expansion factor section corresponding to the data item of the established year is preset to be (0.5,1), and the first quantization function corresponding to the data item of the established year enables the matching degree (0,1) to be uniformly distributed in the corresponding first quantization section, the matching degree of the application enterprise in the established year of 4 years can be calculated to be 1. Similarly, if the first spreading factor interval corresponding to the data item of the sales volume in the last year is preset to be (0.6,1), and the first quantization function corresponding to the data item of the sales volume in the last year makes the matching degree (0,1) uniformly distributed in the corresponding first quantization interval, the matching degree corresponding to the sales volume in the last year of the application enterprise of 1200 ten thousand can be calculated to be 0.5.

And step A5, calculating the total matching degree of the loan application enterprises corresponding to the financial products according to the weight of each data item.

In this step, for example, the weights of the three data items are 0.3,0.2, and 0.5 in sequence from front to back, so that the total matching degree of the loan application enterprise corresponding to the financial product is 0.75 × 0.3+1 × 0.2+0.5 × 0.5 — 0.675, that is, 67.5%.

In another situation, the intelligent recommendation system collects the historical records of loans made by banks to small and medium-sized micro-enterprises in a period of time in the past, the historical records contain basic information, operation data, loan amount and other information of the small and medium-sized micro-enterprises which have loaned the money, the data of the loan historical records can be compared with the information contained in the incoming application, and the matching degree of the loan historical records is calculated, so that the bank with the highest matching degree is selected. The loan history record can be used for calculating the loan strategy of each bank for small and medium-sized micro enterprises, and the bank recommending the loan history record can improve the success rate of credit granting application.

And step S502, sending the incoming application to a bank with the highest matching degree to make a credit application.

Optionally, in another embodiment, after the step S501, the following steps S503 to S504 are further included:

step S503, screening out banks with matching degree higher than a set threshold value;

step S504, the banks meeting the conditions are sorted according to the matching degree from high to low;

correspondingly, the following steps are also included after step S502:

step S505, receiving feedback information of a bank to judge whether the credit application is approved, if so, ending the process, otherwise, entering step S506;

in this step, the feedback information is fed back by the staff at the bank end through the bank terminal 300.

And S506, sending the incoming application to a bank with a lower matching degree to make a credit application, continuously receiving feedback information of the bank to judge whether the credit application passes the examination and approval, if so, ending the process, and otherwise, returning to the step S505.

And the steps S505 to S506 are circularly carried out until the bank passes the examination and approval or all banks corresponding to the financial products with the matching degree higher than the set threshold value pass the examination and approval. The probability of passing the credit application can be improved through the steps.

Optionally, referring to fig. 3, the information verification on the loan application enterprise in step S402 includes the following steps S601 to S604:

step S601, verifying whether the enterprise information contained in the incoming application is correct;

step S602, when the enterprise information contained in the incoming application is verified correctly, sending verification information to the loan application enterprise for secondary verification through a verified reliable path;

in this step, the verified reliable path may be in the form of mailbox verification, short message verification, etc., and the mailbox number and the short message number corresponding to the verified reliable path are handled by the loan application enterprise on-line to ensure the official property and reliability.

Step S603, receiving secondary verification information fed back by the loan application enterprise and judging whether the secondary verification information meets the conditions;

when the secondary verification information fed back by the loan application enterprise meets the condition, the information is verified in step S604.

Through the steps S601-S604, the identity of the loan application enterprise can be checked for the second time, and illegal persons are prevented from falsely using the enterprise name to execute illegal operations.

Optionally, referring to fig. 4, the wind control initial review specifically includes the following step S701:

step S701, auditing each item of business data included in the enterprise information included in the incoming application, and determining whether there is abnormal data in the business data.

Specifically, referring to FIG. 5, the step S701 includes the following steps S701a-S701 c:

step S701a, extracting industry information and main operation product information in the enterprise information;

step S701b, capturing a reference range of each item of operation data of corresponding industries and main operation products from a public database;

in the step, the captured data serving as the reference range is from a public database with higher credibility or authority, and the captured data can reflect the overall market situation of the industry and the main and subordinate products and can be used as a credible reference for evaluating the business situation of the enterprise.

Step S701c, sequentially determining whether each operation data falls within the reference range, if yes, the operation data is normal data, otherwise, the operation data is abnormal data.

Optionally, the following steps S702 to S706 are further included after step S701:

step S702, when abnormal data exists, generating a supplementary certificate file list according to the abnormal data;

step S703 of sending the supplementary certificate manifest to the enterprise terminal 200 of the loan application enterprise;

step S704, receiving a supplementary certificate of a loan application enterprise;

in this step, the supplementary certificate is uploaded and sent by the enterprise end staff through the enterprise terminal 200, and the supplementary certificate is generally a bill, a contract and other materials that can prove the financial data of the enterprise.

Step S705, verifying the credibility and validity of the supplementary certificate file through the operation instruction of the user;

in this step, the verification operation on the supplementary certificate is output to the display interface by the docking device 100 and is completed by the staff, and the staff obtains the verification result after verification and sends a corresponding operation instruction to the docking device 100 to indicate that the material is authentic and valid or not.

When the credibility and the validity of the supplementary certification file both meet the conditions, determining that the loan application enterprise passes the wind control preliminary examination in step S706;

if the reliability and validity of the supplementary certificate do not meet the conditions, the article application is rejected in step S707.

The process can open a self-certification channel for the loan application enterprises, so that the enterprises can verify the reason that the operation condition of the enterprises deviates from the overall market quotation greatly, and if the operation condition is reasonable, the enterprises can pass the wind control initial examination and are continuously examined by the bank which sends the operation condition to the next step, thereby avoiding the situation that the loan channel of small and medium-sized enterprises is closed once and complaints are not made.

Optionally, referring to fig. 6, the wind control preliminary review further includes the following steps S801 to S804:

step S801, obtaining public data of each dimension of a loan application enterprise from a public database;

specifically, the docking device 100 collects the public data of each dimension of the loan application enterprise from the public data source by using the MongoDB database (other NoSQL databases may be used as well), and constructs an enterprise information-based database. The MongoDB database can collect data with complex structure types and is suitable for storing the public data of each dimension of the loan application enterprises. The public data sources comprise an enterprise business database, an invoice database, a tax database and a litigation record database. The public data of each dimension comprises basic information such as industrial and commercial information, management information, operation data and the like, and also comprises various types of risk information, wherein the risk information comprises legal action, administrative penalty, abnormal operation, information lost of credit, executed information, delinquent wages and the like.

Step S802, calculating the risk value of the loan application enterprise according to the public data of each dimension of the loan application enterprise;

in this step, the docking device 100 sequentially extracts the data of each loan application enterprise from the enterprise information database and calculates the risk value of the enterprise according to a preset risk assessment model.

Specifically, the step of calculating the risk value of the enterprise according to the preset risk assessment model comprises the following steps B1-B4:

step B1, determining the reference value of each risk information data according to the basic information of the loan application enterprise;

for example, if the preset rule is to determine the reference value of the risk information of each dimension according to the data of the total sales of the previous year in the operation data, the following example only takes the legal litigation times as an example, the risk information of other dimensions can be analogized, and if the selection rule of the reference value is as follows: when the total sales of the last year is between 0 and 1000 ten thousand, the reference value of the legal action times is 5; when the total sale amount in the last year is between 1000-; when the total sales of the last year is more than 5000 ten thousand, the reference value of the legal action times is 15. If the total sales of the first enterprise in the last year is 3000 ten thousand, the reference value of the legal action times of the first enterprise can be determined to be 10.

Step B2, calculating a second quantifiable interval according to the reference value of the risk information data;

in this step, the second quantifiable interval is calculated by multiplying the reference value of the risk information data by a preset second expansion factor interval, and if the value of the second expansion factor interval corresponding to the number of times of legal action is (0.5,1.2), the second quantifiable interval corresponding to the number of times of legal action is (5, 12).

And step B3, calculating the risk value according to the actual data of each risk information data and the second quantization function thereof.

The second quantifiable interval (5,12) means that if the number of lawsuits of the loan application enterprise is equal to or less than 5, the risk value corresponding to the risk information data, which is the number of lawsuits, is 0, and if the number of lawsuits of the loan application enterprise is equal to or more than 12, the risk value corresponding to the risk information data, which is the number of lawsuits, is 1, and if the number of lawsuits of the loan application enterprise is within the interval (5,12), the risk value needs to be calculated according to the second quantifiable function. If the number of lawsuits of the loan application company is actually 7 and the second quantization function uniformly distributes the risk values (0,1) in the intervals (5,12), the risk value corresponding to the actual number of lawsuits of the loan application company is 0.29. By analogy, the risk values corresponding to other risk information data can be calculated;

and step B4, carrying out weighted calculation according to the weight of each risk information data and the risk value thereof to obtain the total risk value of the loan application enterprise.

In this step, the weighted calculation is to calculate the sum of the products of the risk values and the weights of the risk information data.

Step S803, judge whether the risk value of the enterprise of applying for loan meets the settlement condition;

when the risk value of the loan application enterprise meets the set condition, passing the risk preliminary examination;

when the risk value of the loan application enterprise does not satisfy the set condition, in step S804, the loan application is rejected.

Example two

Referring to fig. 7, which is a schematic diagram illustrating program modules of a docking apparatus 100 according to another embodiment of the present invention, the docking apparatus 100 may include or be divided into one or more program modules, and the one or more program modules are stored in a storage medium and executed by one or more processors to implement the present invention and implement the docking method of the enterprise loan application. The program module referred to in the embodiment of the present invention refers to a series of computer program instruction segments capable of performing specific functions, and is more suitable for describing the execution process of the docking method of the enterprise loan application in a storage medium than the program itself. The following description will specifically describe the functions of the program modules of the present embodiment:

the receiving module 101 receives a request for a loan application enterprise;

here, the incoming application includes information that can reflect the basic situation of the loan application enterprise, such as the basic information of the loan application enterprise, the affiliated industry, the main product, and the operating situation, and also includes specific loan detail information such as the required loan amount and the loan purpose of the loan application enterprise, the person of the loan application enterprise generally submits the incoming application in a form of filling relevant information on line at the enterprise terminal 200 and uploading corresponding vouchers, or submits the incoming application in a form of mails or the like, and the receiving module 101 receives the information filled on line by the loan application enterprise and the uploaded vouchers or receives corresponding mails.

The initial review module 102 is used for carrying out information verification and wind control initial review on the loan application enterprises;

in this step, the information verification process is used to verify whether the basic information of the loan application enterprise is correct, the validity of the login path of the enterprise user, and the like, the wind control initial review process is used to preliminarily evaluate the risk degree of the loan application enterprise according to the information of the industry, the main operation product, the operation condition, and the like of the enterprise and other available public information, and the initial review module 102 can screen out part of the loan application enterprises with high obvious risk through the wind control initial review so as to save subsequent processing flows and avoid the application of computing resources and subsequent bank audit resources to future article applications without prospects.

And the intelligent routing module 103 is used for sending the incoming application to an adaptive bank for credit application through an intelligent recommendation system when the loan application enterprise passes the information verification and wind control initial review.

Here, the intelligent recommendation system is an intelligent recommendation system for a bank that is suitable for intelligent recommendation according to the self condition of a loan application enterprise, and sends an incoming application of the enterprise to the bank terminal 300 of the corresponding bank, and the bank terminal 300 staff further checks the received credit granting application. Referring to fig. 2, the intelligent routing module 103 sends the incoming application to the adapted bank for a credit application through the intelligent recommendation system, including the following steps S501 to S502:

step S501, the intelligent routing module 103 compares the data of each condition of the loan application enterprise with the conditions of each financial product of each bank or the historical loan record data of each bank to obtain the matching degree of each bank;

in one embodiment, the intelligent recommendation system for calculating the matching degree of the incoming application with each financial product comprises the following steps a1-a 5:

step A1, the intelligent routing module 103 obtains financial products meeting the conditions according to the data of the required loan amount in the incoming application and the preset pre-screening rules;

step A2, the intelligent routing module 103 obtains the condition information of the financial product, extracts the data items contained in the condition information and the numerical conditions corresponding to the data items;

data item	Numerical conditions
		Registering funds	Not less than 2000 ten thousand
Year of establishment	More than or equal to 3 years
		Sales volume in last year	≥1500All the details of

Step A3, the intelligent routing module 103 extracts the corresponding data item and the corresponding numerical value from the incoming application;

Step a4, the intelligent routing module 103 calculates a first quantifiable interval according to a critical value of a numerical condition of the data item, and calculates a matching degree of each data item according to a first quantification function;

In step a5, the intelligent routing module 103 calculates the total matching degree of the loan application enterprise corresponding to the financial product according to the weight of each data item.

In another situation, the intelligent recommendation system collects the history of loans made by each bank to the small and medium-sized micro-enterprises in a period of time in the past, the history includes the basic information, the operation data, the loan amount and other information of the small and medium-sized micro-enterprises which are loaned to money, the intelligent routing module 103 compares the data of the loan history with the information included in the incoming application, and calculates the matching degree of the loan history, so that the bank with the highest matching degree is selected. The loan history record can be used for calculating the loan strategy of each bank for small and medium-sized micro enterprises, and the bank recommending the loan history record can improve the success rate of credit granting application.

Step S502, the intelligent routing module 103 sends the incoming application to the bank with the highest matching degree to make a credit application.

correspondingly, the following steps are also included after step S502:

And S506, sending the incoming application to a bank with a lower matching degree for credit application, continuously receiving feedback information of the bank, judging whether the credit application passes the examination and approval, if so, ending the process, otherwise, returning to the step S505.

Optionally, referring to fig. 3, the information verification performed by the review module 102 on the loan application enterprise includes the following steps S601-S604:

when the secondary verification information fed back by the loan application enterprise meets the condition, in step S604, the primary review module 102 passes the information verification.

Optionally, referring to fig. 4, the wind-controlled preliminary review performed by the preliminary review module 102 specifically includes the following step S701:

in this step, the data captured by the initial review module 102 as the reference range is from a public database with higher credibility or authority, and the data captured by the initial review module 102 can reflect the overall market situation of the industry and the main products, and can be used as a credible reference for evaluating the business situation of the enterprise.

When the credibility and the validity of the supplementary certification file both meet the conditions, in step S706, the preliminary review module 102 determines that the loan application enterprise passes the wind control preliminary review;

when the reliability and validity of the supplementary certificate do not meet the conditions, the initial review module 102 rejects the incoming item application in step S707.

Optionally, referring to fig. 6, the wind control preliminary review performed by the preliminary review module 102 further includes the following steps S801-S804:

specifically, the pre-review module 102 collects the dimensional public data of the loan application enterprise from public data sources using the MongoDB database (other NoSQL databases may be used as well), and constructs an enterprise-based information database. The MongoDB database can collect data with complex structure types and is suitable for storing the public data of each dimension of the loan application enterprises. The public data sources comprise an enterprise business database, an invoice database, a tax database and a litigation record database. The public data of each dimension comprises basic information such as industrial and commercial information, management information, operation data and the like, and also comprises various types of risk information, wherein the risk information comprises legal action, administrative penalty, abnormal operation, information lost of credit, executed information, delinquent wages and the like.

in this step, the initial review module 102 sequentially extracts the data of each loan application enterprise from the enterprise information database and calculates the risk value of the enterprise according to a preset risk assessment model.

step B1, the initial review module 102 determines the reference value of each risk information data according to the basic information of the loan application enterprise;

Step B2, the preliminary examination module 102 calculates a second quantifiable interval according to the reference value of the risk information data;

In step B3, the initial review module 102 calculates the risk value according to the actual data of each risk information data and the second quantization function thereof.

and step B4, the initial review module 102 performs weighted calculation according to the weight and the risk value of each risk information data to obtain the total risk value of the loan application enterprise.

EXAMPLE III

Fig. 8 is a schematic diagram of a hardware architecture of a computer apparatus 900 according to a third embodiment of the present invention. In the present embodiment, the computer apparatus 900 is an apparatus capable of automatically performing numerical calculation and/or information processing according to an instruction set or stored in advance. As shown, the computer device 900 includes, but is not limited to, at least a memory 901, a processor 902, a network interface 903, and a docking arrangement 904, which may be communicatively coupled to each other via a system bus. Wherein:

in this embodiment, the memory 901 includes at least one type of computer-readable storage medium including a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the storage 901 may be an internal storage unit of the computer device 900, such as a hard disk or a memory of the computer device 900. In other embodiments, the memory 901 may also be an external storage device of the computer device 900, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. provided on the computer device 900. Of course, the memory 901 may also include both internal and external storage devices for the computer device 900. In this embodiment, the memory 901 is generally used for storing an operating system and various application software installed in the computer device 900, such as a program code of the docking apparatus 904. Further, the memory 901 may also be used to temporarily store various types of data that have been output or are to be output.

Processor 902 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 902 generally operates to control the overall operation of the computer device 900. In this embodiment, the processor 902 is configured to execute the program codes stored in the memory 901 or process data, for example, execute the docking device 904, so as to implement the docking method of the enterprise loan application in the first embodiment.

The network interface 903 may comprise a wireless network interface or a wired network interface, and the network interface 903 is typically used for establishing a communication link between the computer apparatus 900 and other electronic devices. For example, the network interface 903 is used to connect the computer apparatus 900 to an external terminal through a network, establish a data transmission channel and a communication connection between the computer apparatus 900 and the external terminal, and the like. The network may be a wireless or wired network such as an Intranet (Intranet), the Internet (Internet), a Global System of Mobile communication (GSM), Wideband Code Division Multiple Access (WCDMA), a 4G network, a 5G network, Bluetooth (Bluetooth), Wi-Fi, and the like.

It is noted that fig. 8 only shows computer device 900 having components 901 and 904, but it is understood that not all of the shown components are required and that more or less components may be implemented instead.

In this embodiment, the docking device 904 stored in the memory 901 may be further divided into one or more program modules, and the one or more program modules are stored in the memory 901 and executed by one or more processors (in this embodiment, the processor 902) to complete the docking method of the enterprise loan application according to the present invention.

Example four

The present embodiment provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application mall, etc., on which a computer program is stored, which when executed by a processor implements the aforementioned docking method for an enterprise loan application.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.

The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims

1. A docking method of a virtual resource application is applied to a docking device of the virtual resource application, and is characterized in that the method comprises the following steps:

receiving a file-in application of a virtual resource application user;

2. The method for interfacing a virtual resource application according to claim 1, wherein the sending the incoming application to the adapted virtual resource subject for a trust application through an intelligent recommendation system comprises:

comparing the data of each condition of the virtual resource application user with the conditions of each virtual resource product of each virtual resource main body or the historical data of each virtual resource main body to obtain the matching degree of each virtual resource main body;

3. The docking method for virtual resource application of claim 2, wherein the obtaining the matching degree of each virtual resource product further comprises:

after sending the incoming application to the virtual resource main body with the highest matching degree for credit application, the method further comprises the following steps:

4. The docking method for virtual resource application as claimed in claim 1, wherein said checking information of the virtual resource application user comprises:

5. The docking method for virtual resource application of claim 1, wherein the wind-controlled initial review comprises:

6. The virtual resource application docking method of claim 5, wherein the verifying the business data included in the user information included in the incoming application and determining whether the business data includes abnormal data comprises:

7. The method for interfacing a virtual resource application according to claim 5, wherein the verifying each operation data included in the user information included in the incoming application and determining whether there is abnormal data in the operation data further comprises:

receiving a supplementary certificate of a virtual resource application user;

8. An apparatus for interfacing a virtual resource application, comprising:

9. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of interfacing a virtual resource application of any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method of interfacing a virtual resource application according to any one of claims 1 to 7.